Khurram123/Urdu-Llama-3.2-3B-Instruct-v1
Khurram123/Urdu-Llama-3.2-3B-Instruct-v1 is a 3.2 billion parameter instruction-tuned causal language model developed by Khurram Pervez (Khurramcoder). Fine-tuned from Meta's Llama-3.2-3B-Instruct, this model is specifically optimized for high-quality Urdu instruction following and generation. It features native Urdu reasoning capabilities, handling translation, creative writing, and QA tasks with cultural nuance, utilizing a 32768 token context length. The model leverages Unsloth and QLoRA for efficient performance, making it suitable for applications requiring robust Urdu language processing.
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Urdu-Llama-3.2-3B-Instruct-v1 Overview
Developed by Khurram Pervez (Khurramcoder), this model is a specialized fine-tuned version of Meta's Llama-3.2-3B-Instruct, designed for advanced Urdu language processing. With 3.2 billion parameters and a 32768 token context length, it focuses on delivering high-quality instruction following and text generation in Urdu.
Key Capabilities
- Native Urdu Reasoning: The model was trained on the
large-traversaal/urdu-instructdataset (51.7k rows), enabling it to perform complex tasks such as translation, creative writing, and question answering with a deep understanding of Urdu cultural nuances. - Efficient Architecture: Fine-tuned using Unsloth and QLoRA, this model achieves powerful performance while maintaining a lightweight footprint, making it efficient for deployment.
- Optimized for Urdu Script: It incorporates the latest Llama 3.2 multilingual tokenizer, which significantly improves its handling and generation of Urdu script.
Good For
- Urdu Instruction Following: Excels at understanding and executing instructions provided in Urdu.
- Urdu Text Generation: Capable of generating high-quality, culturally relevant Urdu text for various applications.
- Translation and QA: Particularly strong in translation tasks involving Urdu and answering questions in Urdu, leveraging its specialized training data.